Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, Florida.
School of Mathematical Sciences, Rochester Institute of Technology, Rochester, New York.
J Cardiovasc Electrophysiol. 2019 May;30(5):758-768. doi: 10.1111/jce.13872. Epub 2019 Feb 11.
Targeting repeating-pattern atrial fibrillation (AF) sources (reentry or focal drivers) can help in patient-specific ablation therapy for AF; however, the development of reliable and accurate tools for locating such sources remains a major challenge. We describe iterative catheter navigation (ICAN) algorithm to locate AF drivers using a conventional circular Lasso catheter.
At each step, the algorithm analyzes 10 bipolar electrograms recoded at a given catheter location and the history of previous catheter movements to determine if the source is inside the catheter loop. If not, it calculates new coordinates and selects a new position for the catheter. The process continues until a source is located. The algorithm was evaluated in a computer model of atrial tissue with various degrees of fibrosis under a broad range of arrhythmia scenarios. The latter included slow and fast reentry, macroreentry, figure-of-eight reentry, and fibrillatory conduction. Depending on the initial distance of the catheter from the source and scenario, it took about 3 to 16 steps to localize an AF source. In 94% of cases, the identified location was within 4 mm from the source, independently of the initial position of the catheter. The algorithm worked equally well in the presence of patchy fibrosis, low-voltage areas, fragmented electrograms, and dominant-frequency gradients.
AF repeating-pattern sources can be localized using circular catheters without the need to map the entire tissue. The proposed algorithm has the potential to become a useful tool for patient-specific ablation of AF sources located outside the pulmonary veins.
针对重复模式心房颤动(AF)的起源(折返或局灶驱动)有助于针对 AF 患者进行特定的消融治疗;然而,开发可靠且准确的定位此类起源的工具仍然是一个主要挑战。我们描述了一种迭代导管导航(ICAN)算法,该算法使用常规的圆形 Lasso 导管定位 AF 驱动源。
在每一步中,该算法分析在给定导管位置记录的 10 个双极电图,并分析先前导管运动的历史,以确定源是否在导管环内。如果不是,则计算新坐标并为导管选择新位置。该过程持续到找到源为止。该算法在具有各种纤维化程度的心房组织计算机模型中进行了评估,并在广泛的心律失常情况下进行了评估。后者包括缓慢和快速折返、大折返、8 字形折返和纤维性传导。根据导管与源的初始距离和场景,定位 AF 源大约需要 3 到 16 步。在 94%的情况下,无论导管的初始位置如何,确定的位置都与源相差 4mm 以内。该算法在存在斑片状纤维化、低电压区、碎裂电图和主导频率梯度的情况下同样有效。
可以使用圆形导管定位 AF 重复模式的起源,而无需对整个组织进行映射。所提出的算法有可能成为定位肺静脉外 AF 源的特定于患者的消融的有用工具。